Johnson, Aaron M

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Now showing 1 - 8 of 8
  • Publication
    Self-Manipulation and Dynamic Transitions for a Legged Robot
    (2014-01-01) Johnson, Aaron M.
    How can we make a robot that can go anywhere on its own? This thesis presents several new behaviors on the RHex robot that greatly increase the variety of obstacles that it can overcome, including vertical jumps, flips, leaps onto and across ledges, aerial reorientations, and proprioceptively-aware behaviors. These behaviors inspire new tools to model and understand their transitional nature, wherein it is no longer useful to think of each step as being an equal part of a steady state gait. Legged robots will necessarily experience a variety of changing contact conditions as they locomote in complex environments epitomized by the rocky, sandy desert. Drawing on the much more mature literature of robot manipulation, this thesis presents the new modeling paradigm of "self-manipulation" that formally generates analytical equations of motion across all contact states. The framework is amenable to many ubiquitous simplifying assumptions (such as rigid bodies, plastic impact, persistent contact, Coulomb friction, and massless limbs) to reduce the complexity of these models despite the obvious physical inaccuracies that each incurs. Nevertheless the models capture enough of the physical world to represent the challenges confronting interesting behaviors in a qualitatively correct manor, including the effects of impulsive transitions between the various contact modes. More than numerical simulation, our goal is the distillation of these physically parametrized models into formal design insights (platform design, behavior design, and controller design), utilizing a variety of analytical and numerical methods. These behaviors are only possible with a robot designed to be both robust and powerful, and they make use of the unique capability of legged machines to interact with the environment in varied and, possibly, unpredictable ways. Careful actuator modeling is needed to achieve such acrobatic results, and so this thesis presents a spectrum of motor sizing tasks to ensure that the platform is up to the task. These tools are used to gain insight into various dynamic transitions for RHex, and we conjecture that their generalization will be of importance for a broad class of legged robots operating in remote and unstructured terrain.
  • Publication
    Disturbance Detection, Identification, and Recovery by Gait Transition in Legged Robots
    (2010-10-01) Johnson, Aaron M; Haynes, Galen Clark; Koditschek, Daniel E
    We present a framework for detecting, identifying, and recovering within stride from faults and other leg contact disturbances encountered by a walking hexapedal robot. Detection is achieved by means of a software contactevent sensor with no additional sensing hardware beyond the commercial actuators’ standard shaft encoders. A simple finite state machine identifies disturbances as due either to an expected ground contact, a missing ground contact indicating leg fault, or an unexpected “wall” contact. Recovery proceeds as necessary by means of a recently developed topological gait transition coordinator. We demonstrate the efficacy of this system by presenting preliminary data arising from two reactive behaviors — wall avoidance and leg-break recovery. We believe that extensions of this framework will enable reactive behaviors allowing the robot to function with guarded autonomy under widely varying terrain and self-health conditions.
  • Publication
    A Hybrid Systems Model for Simple Manipulation and Self-Manipulation Systems
    (2016-09-01) Johnson, Aaron M.; Burden, Sam; Koditschek, Daniel E
    Rigid bodies, plastic impact, persistent contact, Coulomb friction, and massless limbs are ubiquitous simplifications introduced to reduce the complexity of mechanics models despite the obvious physical inaccuracies that each incurs individually. In concert, it is well known that the interaction of such idealized approximations can lead to conflicting and even paradoxical results. As robotics modeling moves from the consideration of isolated behaviors to the analysis of tasks requiring their composition, a mathematically tractable framework for building models that combine these simple approximations yet achieve reliable results is overdue. In this paper we present a formal hybrid dynamical system model that introduces suitably restricted compositions of these familiar abstractions with the guarantee of consistency analogous to global existence and uniqueness in classical dynamical systems. The hybrid system developed here provides a discontinuous but self-consistent approximation to the continuous (though possibly very stiff and fast) dynamics of a physical robot undergoing intermittent impacts. The modeling choices sacrifice some quantitative numerical efficiencies while maintaining qualitatively correct and analytically tractable results with consistency guarantees promoting their use in formal reasoning about mechanism, feedback control, and behavior design in robots that make and break contact with their environment. For more information: Kod*Lab
  • Publication
    Legged Self-Manipulation
    (2013-01-01) Johnson, Aaron; Koditschek, Daniel E
    This paper introduces self-manipulation as a new formal design methodology for legged robots with varying ground interactions... This work was supported by the ARL/GDRS RCTA project under Cooperative Agreement Number W911NF-10–2−0016. For further information, visit Kod*lab.
  • Publication
    Autonomous Legged Hill and Stairwell Ascent
    (2011-11-01) Johnson, Aaron M; Hale, Matthew T; Koditschek, Daniel E; Haynes, G. C.
    This paper documents near-autonomous negotiation of synthetic and natural climbing terrain by a rugged legged robot, achieved through sequential composition of appropriate perceptually triggered locomotion primitives. The first, simple composition achieves autonomous uphill climbs in unstructured outdoor terrain while avoiding surrounding obstacles such as trees and bushes. The second, slightly more complex composition achieves autonomous stairwell climbing in a variety of different buildings. In both cases, the intrinsic motor competence of the legged platform requires only small amounts of sensory information to yield near-complete autonomy. Both of these behaviors were developed using X-RHex, a new revision of RHex that is a laboratory on legs, allowing a style of rapid development of sensorimotor tasks with a convenience near to that of conducting experiments on a lab bench. Applications of this work include urban search and rescue as well as reconnaissance operations in which robust yet simple-to-implement autonomy allows a robot access to difficult environments with little burden to a human operator.
  • Publication
    Semi-autonomous exploration of multi-floor buildings with a legged robot
    (2015-05-01) Wenger, Garrett; Johnson, Aaron; Taylor, Camilo Jose; Koditschek, Daniel E
    This paper presents preliminary results of a semi-autonomous building exploration behavior using the hexapedal robot RHex. Stairwells are used in virtually all multi-floor buildings, and so in order for a mobile robot to effectively explore, map, clear, monitor, or patrol such buildings it must be able to ascend and descend stairwells. However most conventional mobile robots based on a wheeled platform are unable to traverse stairwells, motivating use of the more mobile legged machine. This semi-autonomous behavior uses a human driver to provide steering input to the robot, as would be the case in, e.g., a tele-operated building exploration mission. The gait selection and transitions between the walking and stair climbing gaits are entirely autonomous. This implementation uses an RGBD camera for stair acquisition, which offers several advantages over a previously documented detector based on a laser range finder, including significantly reduced acquisition time. The sensor package used here also allows for considerable expansion of this behavior. For example, complete automation of the building exploration task driven by a mapping algorithm and higher level planner is presently under development. For more information: Kod*lab
  • Publication
    Parametric Jumping Dataset on the RHex Robot
    (2012-01-01) Johnson, Aaron M; Koditschek, Daniel E
    This report presents the apex state achieved after performing a variety of jumps with the XRL robot. A full account of the behaviors and the theoretical basis is given in another paper, this document is intended to simply provide higher resolution copies of those figures, and present the results in numerical form.
  • Publication
    X-RHex: A Highly Mobile Hexapedal Robot for Sensorimotor Tasks
    (2010-11-04) Galloway, Kevin C; Haynes, Galen Clark; Ilhan, B. Deniz; Johnson, Aaron M; Knopf, Ryan; Lynch, Goran A; Plotnick, Benjamin N; White, Mackenzie; Koditschek, Daniel E
    We report on the design and development of X-RHex, a hexapedal robot with a single actuator per leg, intended for real-world mobile applications. X-RHex is an updated version of the RHex platform, designed to offer substantial improvements in power, run-time, payload size, durability, and terrain negotiation, with a smaller physical volume and a comparable footprint and weight. Furthermore, X-RHex is designed to be easier to build and maintain by using a variety of commercial off-the-shelf (COTS) components for a majority of its internals. This document describes the X-RHex architecture and design, with a particular focus on the new ability of this robot to carry modular payloads as a laboratory on legs. X-RHex supports a variety of sensor suites on a small, mobile robotic platform intended for broad, general use in research, defense, and search and rescue applications. Comparisons with previous RHex platforms are presented throughout, with preliminary tests indicating that the locomotive capabilities of X-RHex can meet or exceed the previous platforms. With the additional payload capabilities of X-RHex, we claim it to be the first robot of its size to carry a fully programmable GPU for fast, parallel sensor processing.